scholarly journals Sapwood Area Related to Tree Size, Tree Age, and Leaf Area Index in Cedrus libani

2018 ◽  
Vol 2 (1) ◽  
pp. 83-91
Author(s):  
Aylin Güney
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Tree Size ◽  
Tree Age ◽  
Area Index ◽  
Sapwood Area ◽  
Cedrus Libani

scholarly journals Biomass Allocation into Woody Parts and Foliage in Young Common Aspen (Populus tremula L.)—Trees and a Stand-Level Study in the Western Carpathians

Forests ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 464 ◽  
Author(s):  
Bohdan Konôpka ◽  
Jozef Pajtík ◽  
Vladimír Šebeň ◽  
Peter Surový ◽  
Katarína Merganičová
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Biomass Allocation ◽  
Tree Size ◽  
Populus Tremula ◽  
Tree Biomass ◽  
Area Index ◽  
Biomass Models ◽  
Maximum Value ◽  
Independent Variable

Our research of common aspen (Populus tremula L.) focused on the forested mountainous area in central Slovakia. Forest stands (specifically 27 plots from 9 sites) with ages between 2 and 15 years were included in measurements and sampling. Whole tree biomass of aspen individuals was destructively sampled, separated into tree components (leaves, branches, stem, and roots), and then dried and weighed. Subsamples of fresh leaves from three crown parts (upper, middle, and lower) were scanned, dried, and weighed. Allometric biomass models with stem base diameter as an independent variable were derived for individual tree components. Basic foliage traits, i.e., leaf mass, leaf area, and specific leaf area, were modelled with regard to tree size and leaf position within the crown. Moreover, biomass stock of the woody parts and foliage as well as the leaf area index were modelled using mean stand diameter as an independent variable. Foliage traits changed with both tree size and crown part. Biomass models showed that foliage contribution to total tree biomass decreased with tree size. The total foliage area of a tree increased with tree size, reaching its maximum value of about 12 m2 for a tree with a diameter of 120 mm. Leaf area index increased with mean stand diameter, reaching a maximum value of 13.5 m2 m−2. Since no data for biomass allocation for common aspen had been available at either the tree or stand levels, our findings might serve for both theoretical (e.g., modelling of growth processes) and practical (forestry and agro-forestry stakeholders) purposes.

The role of stand density on growth efficiency, leaf area index, and resin flow in southwestern ponderosa pine forests

2007 ◽  
Vol 37 (2) ◽  
pp. 343-355 ◽  
Author(s):  
Nate G. McDowell ◽  
Henry D. Adams ◽  
John D. Bailey ◽  
Thomas E. Kolb
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Ponderosa Pine ◽  
Basal Area ◽  
Stand Density ◽  
Growth Efficiency ◽  
Resin Flow ◽  
Area Index ◽  
Sapwood Area ◽  
Ponderosa Pine Forests

We examined the response of growth efficiency (GE), leaf area index (LAI), and resin flow (RF) to stand density manipulations in ponderosa pine ( Pinus ponderosa Dougl. ex Laws.) forests of northern Arizona, USA. The study used a 40 year stand density experiment including seven replicated basal area (BA) treatments ranging from 7 to 45 m2·ha–1. Results were extended to the larger region using published and unpublished datasets on ponderosa pine RF. GE was quantified using basal area increment (BAI), stemwood production (NPPs), or volume increment (VI) per leaf area (Al) or sapwood area (As). GE per Al was positively correlated with BA, regardless of numerator (BAI/Al, NPPs/Al, and VI/Al; r2 = 0.84, 0.95, and 0.96, respectively). GE per As exhibited variable responses to BA. Understory LAI increased with decreasing BA; however, total (understory plus overstory) LAI was not correlated with BA, GE, or RF. Opposite of the original research on this subject, resin flow was negatively related to GE per Al because Al/As ratios decline with increasing BA. BAI, and to a lesser degree BA, predicted RF better than growth efficiency, suggesting that the simplest measurement with the fewest assumptions (BAI) is also the best approach for predicting RF.

Foliage and canopy characteristics in relation to aboveground dry matter increment of seven jack pine provenances

1986 ◽  
Vol 16 (3) ◽  
pp. 464-470 ◽  
Author(s):  
S. Magnussen ◽  
V. G. Smith ◽  
C. W. Yeatman
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Matter ◽  
Basal Area ◽  
Jack Pine ◽  
Tree Size ◽  
Stem Volume ◽  
Dry Matter Content ◽  
Cross Sectional ◽  
Area Index

This paper reports on foliage and tree size data collected in 1984 in an Ontario Pinusbanksiana Lamb, (jack pine) provenance trial established in 1954 at the Petawawa National Forestry Institute, Chalk River, Ont. The ratio of total needle area to needle dry weight of seven provenances showed a substantial within-tree, between-tree, and between-provenance variation that was associated with position within the tree and the average provenance tree size. Provenance mean values ranged from 11.7 to 14.3 m2/kg. The highest values were found in the tallest trees. Tree size and dry matter content varied significantly among provenances, but the relative growth rates of stem volume and aboveground biomass between the ages of 29 and 34 years averaged 5.7 and 4.9% per year in all provenances respectively. Aboveground dry matter production per hectare per year increased linearly with increasing projected leaf area index. The average increase was 1.9 t dry matter per l m2 increase in the leaf area index. Projected leaf area indices for optimally stocked stands averaged 5.0 m2/m2. The results indicated an almost constant net assimilation rate of 1.9 g aboveground dry matter per square decimetre of projected foliage per year in all provenances. Canopy foliage area was strongly correlated with basal area at 1.3 m and stem cross-sectional area at the base of the live crown. Total foliage area per unit basal area averaged 0.31 m2/cm2 at breast height and 0.70 m2/cm2 in the live crown. No significant differences were found between provenances.

scholarly journals The relationship between leaf area and basal area growth in jack and red pine trees

1996 ◽  
Vol 72 (2) ◽  
pp. 170-175 ◽  
Author(s):  
Margaret Penner ◽  
Godelieve Deblonde
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Basal Area ◽  
Growth Efficiency ◽  
Jack Pine ◽  
Red Pine ◽  
Area Index ◽  
Sapwood Area ◽  
Basal Area Growth ◽  
Area Growth

Relationships between leaf area and sapwood area, sapwood area and basal area, and leaf area and basal area growth are determined for jack pine and red pine. The relationships vary with species and stand origin. Growth efficiency (basal area growth per unit leaf area) is relatively independent of tree size under all but the densest conditions. Observed changes in the leaf area to leaf mass ratio from July to October indicate that allometric relationships vary seasonally. A procedure is outlined for obtaining estimates of stand leaf area index (LAI). These estimates may be used to calibrate instruments that measure LAI and, subsequently, to predict forest productivity. Key words: leaf area index, basal area, growth efficiency, red pine, jack pine, sapwood area

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

Sign in / Sign up

Export Citation Format

Share Document